b'Amy Zhang'

research

∙ 06/07/2023

Generalization Across Observation Shifts in Reinforcement Learning

Learning policies which are robust to changes in the environment are cri...

0 Anuj Mahajan, et al. ∙

research

∙ 05/26/2023

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem

Training multiple agents to coordinate is an important problem with appl...

0 Paul Barde, et al. ∙

research

∙ 05/23/2023

Sequence Modeling is a Robust Contender for Offline Reinforcement Learning

Offline reinforcement learning (RL) allows agents to learn effective, re...

0 Prajjwal Bhargava, et al. ∙

research

∙ 05/17/2023

Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor

Social media platforms moderate content for each user by incorporating t...

0 Shagun Jhaver, et al. ∙

research

∙ 04/03/2023

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning

In goal-reaching reinforcement learning (RL), the optimal value function...

0 Tongzhou Wang, et al. ∙

research

∙ 04/02/2023

GitHub OSS Governance File Dataset

Open-source Software (OSS) has become a valuable resource in both indust...

0 Yibo Yan, et al. ∙

research

∙ 03/28/2023

BC-IRL: Learning Generalizable Reward Functions from Demonstrations

How well do reward functions learned with inverse reinforcement learning...

0 Andrew Szot, et al. ∙

research

∙ 03/20/2023

Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement

Object rearrangement is a challenge for embodied agents because solving ...

0 Michael Chang, et al. ∙

research

∙ 03/17/2023

Confidence-aware 3D Gaze Estimation and Evaluation Metric

Deep learning appearance-based 3D gaze estimation is gaining popularity ...

0 Qiaojie Zheng, et al. ∙

research

∙ 02/16/2023

Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods

It is well known that Reinforcement Learning (RL) can be formulated as a...

0 Harshit Sikchi, et al. ∙

research

∙ 02/07/2023

Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability

Goal-conditioned reinforcement learning (GCRL) refers to learning genera...

0 Hanlin Zhu, et al. ∙

research

∙ 01/05/2023

Do Users Want Platform Moderation or Individual Control? Examining the Role of Third-Person Effects and Free Speech Support in Shaping Moderation Preferences

This study examines social media users' preferences for the use of platf...

0 Shagun Jhaver, et al. ∙

research

∙ 12/21/2022

Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning

Traditional approaches to RL have focused on learning decision policies ...

0 Chris Lengerich, et al. ∙

research

∙ 10/27/2022

LAD: Language Augmented Diffusion for Reinforcement Learning

Learning skills from language provides a powerful avenue for generalizat...

0 Edwin Zhang, et al. ∙

research

∙ 10/03/2022

Latent State Marginalization as a Low-cost Approach for Improving Exploration

While the maximum entropy (MaxEnt) reinforcement learning (RL) framework...

0 Dinghuai Zhang, et al. ∙

research

∙ 07/20/2022

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Recommender systems are the algorithms which select, filter, and persona...

0 Jonathan Stray, et al. ∙

research

∙ 06/30/2022

Denoised MDPs: Learning World Models Better Than the World Itself

The ability to separate signal from noise, and reason with clean abstrac...

8 Tongzhou Wang, et al. ∙

research

∙ 04/27/2022

Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning

Building generalizable goal-conditioned agents from rich observations is...

0 Philippe Hansen-Estruch, et al. ∙

research

∙ 02/17/2022

Designing Word Filter Tools for Creator-led Comment Moderation

Online social platforms centered around content creators often allow com...

0 Shagun Jhaver, et al. ∙

research

∙ 02/14/2022

Robust Policy Learning over Multiple Uncertainty Sets

Reinforcement learning (RL) agents need to be robust to variations in sa...

2 Annie Xie, et al. ∙

research

∙ 02/11/2022

Online Decision Transformer

Recent work has shown that offline reinforcement learning (RL) can be fo...

0 Qinqing Zheng, et al. ∙

research

∙ 01/09/2022

Information Borrowing in Regression Models

Model development often takes data structure, subject matter considerati...

0 Amy Zhang, et al. ∙

research

∙ 11/18/2021

A Survey of Generalisation in Deep Reinforcement Learning

The study of generalisation in deep Reinforcement Learning (RL) aims to ...

58 Robert Kirk, et al. ∙

research

∙ 11/15/2021

Learning Representations for Pixel-based Control: What Matters and Why?

Learning representations for pixel-based control has garnered significan...

0 Manan Tomar, et al. ∙

research

∙ 10/13/2021

Block Contextual MDPs for Continual Learning

In reinforcement learning (RL), when defining a Markov Decision Process ...

8 Shagun Sodhani, et al. ∙

research

∙ 08/27/2021

Designing for Multiple Centers of Power: A Taxonomy of Multi-level Governance in Online Social Platforms

Many have criticized the centralized and unaccountable governance of pro...

0 Shagun Jhaver, et al. ∙

research

∙ 07/13/2021

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability

Generalization is a central challenge for the deployment of reinforcemen...

5 Dibya Ghosh, et al. ∙

research

∙ 06/22/2021

Provably Efficient Representation Learning in Low-rank Markov Decision Processes

The success of deep reinforcement learning (DRL) is due to the power of ...

27 Weitong Zhang, et al. ∙

research

∙ 04/20/2021

MBRL-Lib: A Modular Library for Model-based Reinforcement Learning

Model-based reinforcement learning is a compelling framework for data-ef...

0 Luis Pineda, et al. ∙

research

∙ 02/19/2021

Model-Invariant State Abstractions for Model-Based Reinforcement Learning

Accuracy and generalization of dynamics models is key to the success of ...

2 Manan Tomar, et al. ∙

research

∙ 02/11/2021

Multi-Task Reinforcement Learning with Context-based Representations

The benefit of multi-task learning over single-task learning relies on t...

18 Shagun Sodhani, et al. ∙

research

∙ 01/27/2021

Pano: Engaging with News using Moral Framing towards Bridging Ideological Divides

Society is showing signs of strong ideological polarization. When pushed...

0 Jessica Wang, et al. ∙

research

∙ 12/09/2020

Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews

Objective: Systematic reviews of scholarly documents often provide compl...

13 Xiaoxiao Li, et al. ∙

research

∙ 12/03/2020

Intervention Design for Effective Sim2Real Transfer

The goal of this work is to address the recent success of domain randomi...

2 Melissa Mozifian, et al. ∙

research

∙ 07/14/2020

Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP

Multi-task reinforcement learning is a rich paradigm where information f...

16 Amy Zhang, et al. ∙

research

∙ 06/18/2020

Learning Invariant Representations for Reinforcement Learning without Reconstruction

We study how representation learning can accelerate reinforcement learni...

9 Amy Zhang, et al. ∙

research

∙ 05/07/2020

Plan2Vec: Unsupervised Representation Learning by Latent Plans

In this paper we introduce plan2vec, an unsupervised representation lear...

8 Ge Yang, et al. ∙

research

∙ 03/12/2020

Invariant Causal Prediction for Block MDPs

Generalization across environments is critical to the successful applica...

2 Amy Zhang, et al. ∙

research

∙ 03/09/2020

Stable Policy Optimization via Off-Policy Divergence Regularization

Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization...

6 Ahmed Touati, et al. ∙

research

∙ 03/02/2020

Out-of-Distribution Generalization via Risk Extrapolation (REx)

Generalizing outside of the training distribution is an open challenge f...

25 David Krueger, et al. ∙

research

∙ 10/02/2019

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Training an agent to solve control tasks directly from high-dimensional ...

18 Denis Yarats, et al. ∙

research

∙ 06/25/2019

Learning Causal State Representations of Partially Observable Environments

Intelligent agents can cope with sensory-rich environments by learning t...

68 Amy Zhang, et al. ∙

research

∙ 11/14/2018

Natural Environment Benchmarks for Reinforcement Learning

While current benchmark reinforcement learning (RL) tasks have been usef...

6 Amy Zhang, et al. ∙

research

∙ 06/20/2018

A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning

The risks and perils of overfitting in machine learning are well known. ...

0 Amy Zhang, et al. ∙

research

∙ 04/27/2018

Decoupling Dynamics and Reward for Transfer Learning

Current reinforcement learning (RL) methods can successfully learn singl...

0 Amy Zhang, et al. ∙

research

∙ 03/01/2018

Composable Planning with Attributes

The tasks that an agent will need to solve often are not known during tr...

0 Amy Zhang, et al. ∙

research

∙ 12/15/2017

Mapping the world population one building at a time

High resolution datasets of population density which accurately map spar...

0 Tobias G. Tiecke, et al. ∙

research

∙ 07/27/2017

Building Detection from Satellite Images on a Global Scale

In the last several years, remote sensing technology has opened up the p...

0 Amy Zhang, et al. ∙

research

∙ 12/08/2016

Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation

Learning from weakly-supervised data is one of the main challenges in ma...

0 Xianming Liu, et al. ∙

research

∙ 08/09/2014

Guess Who Rated This Movie: Identifying Users Through Subspace Clustering

It is often the case that, within an online recommender system, multiple...

0 Amy Zhang, et al. ∙

Amy Zhang

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